Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00088
N. Kondo, T. Hatanaka, T. Matsuda
In order to improve student's learning, it is important to understand how students learn outside the classroom and to support each student's individual needs. In this research, learning processes and learning outcomes were analyzed in association with the learning record data of online notes, for lessons centered on learning activities creating online notes using Scrapbox. By using the Scrapbox data log, it was possible to quantify and visualize how a knowledge network was constructed using online notes. In addition, deep learning with an awareness of the relationship between different types of knowledge enhanced self-assessment of understanding.
{"title":"An Analysis of Learning Processes on Online Notes using Scrapbox","authors":"N. Kondo, T. Hatanaka, T. Matsuda","doi":"10.1109/IIAI-AAI.2019.00088","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00088","url":null,"abstract":"In order to improve student's learning, it is important to understand how students learn outside the classroom and to support each student's individual needs. In this research, learning processes and learning outcomes were analyzed in association with the learning record data of online notes, for lessons centered on learning activities creating online notes using Scrapbox. By using the Scrapbox data log, it was possible to quantify and visualize how a knowledge network was constructed using online notes. In addition, deep learning with an awareness of the relationship between different types of knowledge enhanced self-assessment of understanding.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115250003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00018
Hualing Yi, Qingyu Xiong, Qinghong Zou, Rui Xu, Kai Wang, Min Gao
Air pollution has a serious impact on daily life. It is necessary to inform the air quality in time to the public in order to take measures in advance. Machine learning methods such as random forest are good at evaluating grades of air quality. We find the distribution of air data is imbalance, which leads to negative effect on random forest classifiers. We propose a random forest method based on samples grouped bootstrap to solve this problem. Then we design three sets of experiments to evaluate the performance of the proposed method. The results of experiments indicate that the proposed method presents an improvement of random forest when both apply on balance datasets. The improvement is very significant when they apply on imbalance datasets, where the new method is much better at classifying minority samples.
{"title":"A Novel Random Forest and its Application on Classification of Air Quality","authors":"Hualing Yi, Qingyu Xiong, Qinghong Zou, Rui Xu, Kai Wang, Min Gao","doi":"10.1109/IIAI-AAI.2019.00018","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00018","url":null,"abstract":"Air pollution has a serious impact on daily life. It is necessary to inform the air quality in time to the public in order to take measures in advance. Machine learning methods such as random forest are good at evaluating grades of air quality. We find the distribution of air data is imbalance, which leads to negative effect on random forest classifiers. We propose a random forest method based on samples grouped bootstrap to solve this problem. Then we design three sets of experiments to evaluate the performance of the proposed method. The results of experiments indicate that the proposed method presents an improvement of random forest when both apply on balance datasets. The improvement is very significant when they apply on imbalance datasets, where the new method is much better at classifying minority samples.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114767396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00099
Yen-lun Chen, Yi-Leh Wu, Cheng-Yuan Tang
In the past, people usually employ the facial feature extraction and shallow learners such as decision trees, SVM, Naive Bayes, etc. to classify faces of different races. Deep learning usually takes lots of time to train. But with the advances in hardware and new algorithm proposed, the training time problem is gradually alleviated. The deep convolutional neural networks have good effect on images classification. In this paper, we use the deep convolutional neural networks to try to solve the problem of classification faces of different racial origin. Because the convolutional neural networks usually require a huge amount of data for training for good performance, such training set of real racial faces is not available to us. As a result of small set of real racial faces, this study proposes to incorporate synthetic facial images in our training set to sufficiently increase the size of the training set. To the best of our knowledge, this study is the first to propose to incorporate synthetic racial faces to train a deep convolutional neural network to classify real racial faces. We compare the performance of only employ synthetic facial images and mixtures of synthetic and real facial images in the training set. Our experiments show that training with only the real facial images (2,500 images) can achieve 91.25% accuracy in classifying faces of three different race origins. However, the classification when training with a mixture of 2,500 real facial images and 15,000 synthetic facial images can be further improved to 98.5% in accuracy.
{"title":"Using Synthetic Images with Deep Convolutional Neural Networks for Racial Face Recognition","authors":"Yen-lun Chen, Yi-Leh Wu, Cheng-Yuan Tang","doi":"10.1109/IIAI-AAI.2019.00099","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00099","url":null,"abstract":"In the past, people usually employ the facial feature extraction and shallow learners such as decision trees, SVM, Naive Bayes, etc. to classify faces of different races. Deep learning usually takes lots of time to train. But with the advances in hardware and new algorithm proposed, the training time problem is gradually alleviated. The deep convolutional neural networks have good effect on images classification. In this paper, we use the deep convolutional neural networks to try to solve the problem of classification faces of different racial origin. Because the convolutional neural networks usually require a huge amount of data for training for good performance, such training set of real racial faces is not available to us. As a result of small set of real racial faces, this study proposes to incorporate synthetic facial images in our training set to sufficiently increase the size of the training set. To the best of our knowledge, this study is the first to propose to incorporate synthetic racial faces to train a deep convolutional neural network to classify real racial faces. We compare the performance of only employ synthetic facial images and mixtures of synthetic and real facial images in the training set. Our experiments show that training with only the real facial images (2,500 images) can achieve 91.25% accuracy in classifying faces of three different race origins. However, the classification when training with a mixture of 2,500 real facial images and 15,000 synthetic facial images can be further improved to 98.5% in accuracy.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127635417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00040
Chih-Hsiang Ko
System and service quality is important in influencing user adoption of technology such as virtual reality. This study explored user satisfaction and classified user expectation of a multi-user virtual reality system by using the Kano model. Focus group discussion was conducted to identify quality requirements such as interactive, immersive, functional and practical attributes. A Kano questionnaire was used to measure user satisfaction for the quality attributes. The result indicated that immersive and functional attributes were classified as must-be requirements. Interactive attributes were classified as one-dimensional and practical attributes as attractive requirements. It is an essential and critical element for a virtual reality system to meet and satisfy user needs.
{"title":"The Quality Satisfaction of A Multi-User Virtual Reality System","authors":"Chih-Hsiang Ko","doi":"10.1109/IIAI-AAI.2019.00040","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00040","url":null,"abstract":"System and service quality is important in influencing user adoption of technology such as virtual reality. This study explored user satisfaction and classified user expectation of a multi-user virtual reality system by using the Kano model. Focus group discussion was conducted to identify quality requirements such as interactive, immersive, functional and practical attributes. A Kano questionnaire was used to measure user satisfaction for the quality attributes. The result indicated that immersive and functional attributes were classified as must-be requirements. Interactive attributes were classified as one-dimensional and practical attributes as attractive requirements. It is an essential and critical element for a virtual reality system to meet and satisfy user needs.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126016762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00129
Xianyao Chen, Hai Xue, Min-Woo Kim, Cheng Wang, H. Youn
As the population aging issue becomes more serious these days, fall detection of the elderly has been attracting a great deal of interests. A fall detection system includes data collection, data pre-processing, feature extraction, feature selection, and then activity classification. In this context the researchers have conducted studies on acceleration-based fall detection using external accelerometer or built-in sensors in smartphone. In this paper a novel approach for fall detection using machine learning technique is proposed, which employs a new pre-processing technique to remove noise from sensor data. It mainly consists of two processes: short-term smoothing to remove the short term vibration and long-term smoothing to smooth sensor readings captured in a longer time window. To detect falls, statistical models are proposed to extract the features. A public dataset, MobiFall, is used for performance evaluation, which contains the data of accelerometer and gyroscope with the orientation along each axis in the smartphone coordination system. With the selected features, the proposed scheme identifies falls from the activities of daily living with a high accuracy of up to 98.3%. Moreover, tFall dataset is also used to perform a cross verification of the proposed scheme.
{"title":"Detection of Falls with Smartphone Using Machine Learning Technique","authors":"Xianyao Chen, Hai Xue, Min-Woo Kim, Cheng Wang, H. Youn","doi":"10.1109/IIAI-AAI.2019.00129","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00129","url":null,"abstract":"As the population aging issue becomes more serious these days, fall detection of the elderly has been attracting a great deal of interests. A fall detection system includes data collection, data pre-processing, feature extraction, feature selection, and then activity classification. In this context the researchers have conducted studies on acceleration-based fall detection using external accelerometer or built-in sensors in smartphone. In this paper a novel approach for fall detection using machine learning technique is proposed, which employs a new pre-processing technique to remove noise from sensor data. It mainly consists of two processes: short-term smoothing to remove the short term vibration and long-term smoothing to smooth sensor readings captured in a longer time window. To detect falls, statistical models are proposed to extract the features. A public dataset, MobiFall, is used for performance evaluation, which contains the data of accelerometer and gyroscope with the orientation along each axis in the smartphone coordination system. With the selected features, the proposed scheme identifies falls from the activities of daily living with a high accuracy of up to 98.3%. Moreover, tFall dataset is also used to perform a cross verification of the proposed scheme.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126635682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00076
M. Yagi, Reiko Murakami, S. Tsuzuku, Mitsue Suzuki, H. Nakano, Katsuaki Suzuki
Japan's nurses have seen an increase in distance learning opportunities, but there is little information on the current situation or associated outcomes. This makes it difficult to appropriately implement measures that support distance learning. This study uses learning analytics based on distance learning logs and learner information to build a learning support program that is suitable for learners in the field of nursing. Our findings show that frequency of logins to a distance-learning course for nurses was related to course completion, as was login frequency to an orientation course and after three months from the course start. These results have implications for implementing support. For instance, educators will check the learner's learning status and provide suitable support as advice and metering. Additionally, these supports were applicable not only nurses but also all health professionals who receive training through distance learning.
{"title":"Using Learning Analytics to Build a Learning Support Program for Distance Learning in Nursing","authors":"M. Yagi, Reiko Murakami, S. Tsuzuku, Mitsue Suzuki, H. Nakano, Katsuaki Suzuki","doi":"10.1109/IIAI-AAI.2019.00076","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00076","url":null,"abstract":"Japan's nurses have seen an increase in distance learning opportunities, but there is little information on the current situation or associated outcomes. This makes it difficult to appropriately implement measures that support distance learning. This study uses learning analytics based on distance learning logs and learner information to build a learning support program that is suitable for learners in the field of nursing. Our findings show that frequency of logins to a distance-learning course for nurses was related to course completion, as was login frequency to an orientation course and after three months from the course start. These results have implications for implementing support. For instance, educators will check the learner's learning status and provide suitable support as advice and metering. Additionally, these supports were applicable not only nurses but also all health professionals who receive training through distance learning.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122509023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00216
Yi-Ting Gau, Kai-Hsiang Yang
Many research indicates that the integration of mobile learning environment can effectively enhance students' motivation for learning. However, instructors adopt appropriate learning strategies is the main factor to help students improve their learning performance. The study expected the Predict-Observe-Explain (POE) teaching strategies in mathematics teaching has significant effects on learning effectiveness and retention. Few studies have explicitly incorporated the POE strategy and collaborative learning approach with mobile learning environment in elementary students' mathematics learning. The 41 fifth graders who participate in this research are assigned to an experimental group and a control group. The students in the experimental group will learn through the POE teaching strategy combined with the collaborative learning approach; while those who participant in control group will learn mathematics through the POE teaching strategy only. The aim of this research focuses on the effects of the POE strategy and collaborative learning approach with mobile learning environment on students' learning achievements, learning attitude, and self-efficacy of mathematics.
{"title":"Design and Evaluation of a Collaborative POE-based Learning Model for Mathematics Learning","authors":"Yi-Ting Gau, Kai-Hsiang Yang","doi":"10.1109/IIAI-AAI.2019.00216","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00216","url":null,"abstract":"Many research indicates that the integration of mobile learning environment can effectively enhance students' motivation for learning. However, instructors adopt appropriate learning strategies is the main factor to help students improve their learning performance. The study expected the Predict-Observe-Explain (POE) teaching strategies in mathematics teaching has significant effects on learning effectiveness and retention. Few studies have explicitly incorporated the POE strategy and collaborative learning approach with mobile learning environment in elementary students' mathematics learning. The 41 fifth graders who participate in this research are assigned to an experimental group and a control group. The students in the experimental group will learn through the POE teaching strategy combined with the collaborative learning approach; while those who participant in control group will learn mathematics through the POE teaching strategy only. The aim of this research focuses on the effects of the POE strategy and collaborative learning approach with mobile learning environment on students' learning achievements, learning attitude, and self-efficacy of mathematics.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124962688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00211
Long-Sheng Chen, Mu-Chen Chen, Yi-Ru Lin
In today's overseas purchasing industry, consumers' preferences and demands have been changing quickly due to fierce market competition. Overseas purchasing agents need to discover the real needs of consumers and to differentiate services or products. Therefore, this study will use the Kano Model to conduct a questionnaire survey, in addition to helping the overseas purchasing industry to quickly understand the true needs of customers, to find the categorization of quality elements that are attractive to consumers. Finally, the results of the study will be provided to the overseas purchasing agents as references for facilitating the service industry to differentiate services and products, and enhance market competitiveness.
{"title":"Customer Needs Analysis for Overseas Purchasing in Taiwan","authors":"Long-Sheng Chen, Mu-Chen Chen, Yi-Ru Lin","doi":"10.1109/IIAI-AAI.2019.00211","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00211","url":null,"abstract":"In today's overseas purchasing industry, consumers' preferences and demands have been changing quickly due to fierce market competition. Overseas purchasing agents need to discover the real needs of consumers and to differentiate services or products. Therefore, this study will use the Kano Model to conduct a questionnaire survey, in addition to helping the overseas purchasing industry to quickly understand the true needs of customers, to find the categorization of quality elements that are attractive to consumers. Finally, the results of the study will be provided to the overseas purchasing agents as references for facilitating the service industry to differentiate services and products, and enhance market competitiveness.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124976278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00226
Megumi Futatsugi, Kyoko Ojima, Y. Takata, Y. Kasahara, Chiho Oyabu, Kimikazu Sugimori
This paper shows a cooperative learning system for financial education using information communication technology (ICT). Financial education has not been spread satisfactorily among consumers. The reason is a lack of both time and teachers. We attempt to solve this problem using a finance support system. This system adopts three approaches to the problem. First, we asked financial specialists to participate in the system as advisors of financial education. Second, we provide an online network system to help the people who do not have enough time. The final approach is a cooperative system in which consumers themselves will help each other. Prior to the system development, we explored consumers' demands using a questionnaire.
{"title":"A Cooperative Learning System for Financial Education Using ICT","authors":"Megumi Futatsugi, Kyoko Ojima, Y. Takata, Y. Kasahara, Chiho Oyabu, Kimikazu Sugimori","doi":"10.1109/IIAI-AAI.2019.00226","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00226","url":null,"abstract":"This paper shows a cooperative learning system for financial education using information communication technology (ICT). Financial education has not been spread satisfactorily among consumers. The reason is a lack of both time and teachers. We attempt to solve this problem using a finance support system. This system adopts three approaches to the problem. First, we asked financial specialists to participate in the system as advisors of financial education. Second, we provide an online network system to help the people who do not have enough time. The final approach is a cooperative system in which consumers themselves will help each other. Prior to the system development, we explored consumers' demands using a questionnaire.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131502699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00037
Kousuke Abe, Yuki Fukawa, Tetsuo Tanaka
For the education of beginning programmers, visual programming that develops programs by combining blocks has attracted significant attention. An environment for generating code in a conventional programming language is also provided. However, existing environments are not fully visualized. In this investigation, we prototyped a development environment for the C language in which users can intuitively understand the concept of variable declarations and include statements, and an execution environment that visualizes the state of evaluation of expressions and changes in the values of variables before and after the execution of the statement. It also has step-forward and step-backward functions. This programming environment is a web application developed with JavaScript. For step-by-step evaluation of an expression, it converts the expression internally to reverse Polish notation and visualizes the change in the terms in the expression. To implement the step-backward function, it has a history-of-execution context. We determined experimentally that students who are not proficient in C can program more accurately and quickly in this environment than with text-based coding.
{"title":"Prototype of Visual Programming Environment for C Language Novice Programmer","authors":"Kousuke Abe, Yuki Fukawa, Tetsuo Tanaka","doi":"10.1109/IIAI-AAI.2019.00037","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00037","url":null,"abstract":"For the education of beginning programmers, visual programming that develops programs by combining blocks has attracted significant attention. An environment for generating code in a conventional programming language is also provided. However, existing environments are not fully visualized. In this investigation, we prototyped a development environment for the C language in which users can intuitively understand the concept of variable declarations and include statements, and an execution environment that visualizes the state of evaluation of expressions and changes in the values of variables before and after the execution of the statement. It also has step-forward and step-backward functions. This programming environment is a web application developed with JavaScript. For step-by-step evaluation of an expression, it converts the expression internally to reverse Polish notation and visualizes the change in the terms in the expression. To implement the step-backward function, it has a history-of-execution context. We determined experimentally that students who are not proficient in C can program more accurately and quickly in this environment than with text-based coding.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131432728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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